Google’s no-code AI app builder, Opal, is expanding globally and getting some big upgrades

Just a couple of months ago, Google Labs unveiled one of its most exciting experiments in a long time: Opal, a tool that lets anyone build their own AI-powered mini-apps using just natural language—no coding required. After an initial, U.S.-only launch, the creativity of early adopters has made one thing clear: Google needs to get this powerful tool into the hands of more people.

Today, Google is doing just that. In a new blog post, the company has announced that it is expanding Opal to 15 new countries and rolling out some powerful new features to make building custom AI apps even easier and more reliable.

Opal goes global

After seeing the “sophisticated, practical and highly creative” apps built by its initial user base, Google is beginning to roll out Opal to a much wider audience. The expansion includes 15 more countries, with notable additions like Canada, India, Japan, South Korea, and Brazil. This is a huge step in getting this powerful, democratized AI tool into the hands of more creators around the world.

Alongside the global expansion, Opal is also getting some significant upgrades based on early user feedback. The two biggest improvements are:

• Advanced no-code debugging: Building a complex workflow can be tricky, and finding out why something isn’t working can be frustrating. Opal now features an improved, visual debugging tool that lets you run your workflow step-by-step and shows you in real-time the exact step where a failure occurred, eliminating the guesswork.
• Faster performance: Google has also made significant under-the-hood improvements to Opal’s speed. Creating new apps is now “dramatically” faster, and complex workflows can now run multiple steps in parallel, reducing the overall wait time for your app to execute.

This is a fantastic sign of momentum for what is arguably one of the most interesting projects to come out of Google Labs. By continuing to expand and refine Opal, Google is doubling down on its effort to democratize AI, giving more people the tools to build their own custom solutions without needing to write a single line of code.